Originally posted on LinkedIn by Greg Rosner. I saw the phrase “linguistic janitorial work” in this Deloitte whitepaper on “AI-augmented government, using cognitive technologies to redesign public sector work”, used to describe the drudgery of translation work that so many translators are required to do today through Post-editing of Machine Translation. And then it hit me what’s really going on. The sad reality over the past several years is that many professional linguists, who have decades of particular industry experience, expertise in professional translation and have earned degrees in writing, whose jobs have been reduced to sentence-by-sentence clean-up of translations that flood out of Google Translate or other Machine Translation (MT) systems.
Neural Machine Translation is everywhere (and not just on this blog). Translators want to know how it will affect their livelihood, and internal localization managers want to know how they can make it work for their translation strategy. Whether you're looking to assess the business applications of neural machine translation, or peek under the hood to see how all the gears fit together, these NMT videos can help you wrap your head around the rising tide that is neural machine translation.